A three-step algorithm is adopted. First, to reduce the random error inherent in the individual data sources, the satellite estimates are combined linearly through the Maximum Likelihood Estimation Method, in which the weighting coefficients are inversely proportional to the individual error variance. To remove the bias, the output of the first step is then blended with the gauge-based analysis through the method of Reynolds (1988), in which the first-step-output and the gauge data are used to define the 'shape' and the magnitude of the precipitation field, respectively. Finally, the blended analysis is adjusted by the monthly GPCP merged analysis of precipitation to make sure that the accumulation of the pentad analysis matches that of the monthly analysis.
The 20-year pentad GPCP merged analysis is applied to investigate the interannual and intraseasonal variations of large-scale precipitation. Preliminary results showed that the pentad analysis is very useful in detecting intrseasonal climate variations.
![](images/flag.png)
![](images/blue_ribbon.png)